We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within the Infrastructure Platforms, you are an integral part of an agile team that works to enhance, build, and deliver trusted data intensive products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
1. Executes creative data intensive software solutions using latest technologies, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
2. Develops secure high-quality production code, and reviews and debugs code written by others
3. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
4. Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
5. Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
6. Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
7. Expert in Java and Spring Boot for backend development and system architecture with product development experience.
8. Proficient in modern front-end frameworks such as React.
9. Advanced experience with relational (SQL) and NoSQL databases, including data modeling and optimization.
10. Hands-on with big data technologies Spark, and Kafka for large-scale data processing.
11. Skilled in designing and implementing scalable microservice's and RESTful APIs.
12. Strong background in cloud platforms and DevOps practices (CI/CD, Docker, Kubernetes).
13. Proven ability in driving best practices and code quality.
14. Experienced in Agile methodologies, sprint planning, and cross-functional collaboration.
15. Excellent problem-solving, analytical, and troubleshooting skills for complex technical challenges.
16. Effective communicator with stakeholders, translating business requirements into robust technical solutions.
Preferred qualifications, capabilities, and skill
17. Experience with GraphQL for advanced API design and data fetching.
18. Knowledge of machine learning frameworks Spark ML and data science workflows.